如何按不符合条件的行名对数据帧进行子集化？

Question

I have a data frame that consists of names and dates. I wish to subset the data frame by names that do not appear in 3 consecutive years. Here is my data frame:

data <- data.frame( Name = c("Dex","Dex","Rex","Rex","Rex","Lex","Lex", "Nex","Nex","Nex"), Year = c(2000, 2001, 2000, 2001, 2002, 2001, 2002, 2000, 2001, 2002 ))

Name Year Dex 2000 Dex 2001 Rex 2000 Rex 2001 Rex 2002 Lex 2001 Lex 2002 Nex 2000 Nex 2001 Nex 2002

This is the desired output:

Name Year Dex 2000 Dex 2001 Lex 2001 Lex 2002

Is there a way to subset data according to conditions that are not met?

Answer 1

In the example, the 'Year' for all unique 'Name' are consecutive. So, an easier option would be to group by 'Name' and filter if the number of distinct 'Year' is less than 3 or the number of rows ( n() ) is less than 3

library(dplyr)
data %>%
   group_by(Name) %>% 
   filter(n_distinct(Year) < 3)
   #or the number of rows
   # filter(n() < 3)
# A tibble: 4 x 2
# Groups:   Name [2]
#  Name   Year
#  <fct> <dbl>
#1 Dex    2000
#2 Dex    2001
#3 Lex    2001
#4 Lex    2002

---

As a general case, after grouping by 'Name', we get the diff erence of adjacent 'Year', check if it is equal to 1 ie 1 year difference, use that in run-length-encoding ( rle ) to find the max imum length of sequence of consecutive 'year' is less than 3 to filter those 'Name' groups

data %>%
   group_by(Name) %>% 
   filter(with(rle(c(TRUE, diff(Year)) == 1), max(lengths[values])) < 3)
# A tibble: 4 x 2
# Groups:   Name [2]
#  Name   Year
#  <fct> <dbl>
#1 Dex    2000
#2 Dex    2001
#3 Lex    2001
#4 Lex    2002